The Halting Probability in Von Neumann Architectures

Abstract

Abstract. Genetic programming (GP) offers a generic method of automatically fusing together classifiers using their receiver operating characteristics (ROC) to yield superior ensembles. We combine decision trees (C4.5) and artificial neural networks (ANN) on a difficult pharmaceutical data mining (KDD) drug discovery application. Specifically predicting inhibition of a P450 enzyme. Training data came from high throughput screening (HTS) runs. The evolved model may be used to predict behaviour of virtual (i.e. yet to be manufactured) chemicals. Measures to reduce over fitting are also described.

Efficient Markov Chain Model of Machine Code Program Execution and Halting

“…In this paper we present the new model in detail and we discuss its implications for genetic programming research. As with [7] we will corroborate our theoretical investigation using a particularly simple computer, the T7. The next section describes the T7 computer.…”

“…In a recent paper [7], we started extending our results to Turing complete linear GP machine code programs. We analysed the formation of the first loop in the programs and whether programs ever leave that loop.…”

“…Finally, to further corroborate our results we developed a first Markov chain model of program execution and halting. Given its complexity and the limitations of space available, however, in [7] we only provided a one-page summary of its structure and results. The results confirmed both the simulations and the " √ L" scaling laws.…”

“…The results confirmed both the simulations and the " √ L" scaling laws. Since [7], we further developed, validated and refined our Markov chain model, developing ways of iterating its transition matrix efficiently. In this paper we present the new model in detail and we discuss its implications for genetic programming research.…”

Finch: A System for Evolving Java (Bytecode)

“…An important issue that must be considered when dealing with the evolution of unrestricted programs is whether they halt-or not (Langdon and Poli, 2006). Whenever Turing-complete programs with arbitrary control flow are evolved, a possibility arises that computation will turn out to be unending.…”